Abhijit Patil (AbhiFutureTech)

AbhiFutureTech

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Location:Pune, Maharashtra

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Abhijit Patil's repositories

Object-detection-via-Tensorflow

Use the Tensorflow Object Detection API with Tensorflow 2

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Neural-Network-Based-Autonomous-Navigation-for-Self-Driving-Robots

This project focuses on developing and implementing neural network algorithms to enable autonomous navigation in self-driving robots.

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Gesture-controlled-robotic-hand-via-CV

This project used computer vision to detects and interprets hand gestures to control robotics hand.

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Robotic-Object-Recongtion-via-CNN-and-Image-Processing

This project aims to develop and implement robust object recognition techniques for robotics applications using CNNs and advanced image processing methods.

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Chat-Bot

Food ordering chatbot using Dialogflow, FastAPI backend, MySQL database, and a responsive frontend. Allows users to place new orders and track existing ones.

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patilabhi20

Config files for my GitHub profile.

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Robotic-Tasks-via-Large-Language-Models

By leveraging the capabilities of LLMs, we aim to enhance the interaction between humans and robots, enabling more intuitive and intelligent robotic operations.

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Human-Robot-Interaction

This project aims to develop and showcase various techniques and algorithms for effective interaction between humans and robots through programming.

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Keras-image-classification-

We will use keras fashion MNIST dataset. This consist of 60000 28X28 pixel images and 10000 test images, these images are classified in one of the 10 categories

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image-classification-via-CNN

Implement different Convolutional Neural Networks (CNN) classifiers using GPU-enabled Tensorflow and Keras API Compare different CNN architectures.

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LLM_project

The LLM (Large Language Model) in Artificial Intelligence project for our Model T-Shirts Store aims to revolutionize the customer experience by leveraging advanced AI technologies

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EDA_project

This repository contains an exploratory data analysis (EDA) project focused on roller coasters. The project involved organizing, cleaning, and visualizing the data to gain insights into roller coasters' characteristics and performance.

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